{"title":"Could the Altman Z-Score Model Detect the Financial Distress in Ghana? Multivariate Discriminant Analysis","authors":"J. MacCarthy, Richard Amoasi-Andoh","doi":"10.22495/cgsrv4i2p1","DOIUrl":null,"url":null,"abstract":"The purpose of this paper is to assess the effectiveness of the Altman Z-score model to discriminate between financially distressed and non-financially distressed manufacturing firms listed on the Ghana Stock Exchange. Eleven firms consisting of two financially distressed and nine non-financially distressed manufacturing firms were analysed. Independent descriptive statistics, independent sample t-test, and multivariate discriminant analysis were the analytical tools used to analyse the hypotheses of this study. The study revealed that working capital/total assets and sales/total assets were the major discriminators of financially distressed firms on the Ghana Stock Exchange. Multivariate discriminant analysis revealed an accuracy rate of 79.9% to detect financially distressed firms in Ghana.","PeriodicalId":11465,"journal":{"name":"Econometrics: Econometric & Statistical Methods - General eJournal","volume":"46 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometrics: Econometric & Statistical Methods - General eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22495/cgsrv4i2p1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The purpose of this paper is to assess the effectiveness of the Altman Z-score model to discriminate between financially distressed and non-financially distressed manufacturing firms listed on the Ghana Stock Exchange. Eleven firms consisting of two financially distressed and nine non-financially distressed manufacturing firms were analysed. Independent descriptive statistics, independent sample t-test, and multivariate discriminant analysis were the analytical tools used to analyse the hypotheses of this study. The study revealed that working capital/total assets and sales/total assets were the major discriminators of financially distressed firms on the Ghana Stock Exchange. Multivariate discriminant analysis revealed an accuracy rate of 79.9% to detect financially distressed firms in Ghana.